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Green Engineering: Journal of Engineering and Applied Science
Published by International Forum of Researchers and Lecturers
ISSN : 30636841     EISSN : 30636833     DOI : 10.70062
Core Subject : Agriculture, Engineering,
Agriculture, Biological Sciences & Forestry Civil Engineering, Building, Construction & Architecture Electrical & Electronics Engineering Engineering
(Green Engineering: Journal of Engineering and Applied Science) [e-ISSN : 3063-6833, p-ISSN : 3063-6841] is an open access Journal published by the IFREL ( Forum of Researchers and Lecturers). Green Engineering accepts manuscripts based on empirical research results, new scientific literature review, and comments/ criticism of scientific papers published by Green Engineering. This journal is a means of publication and a place to share research and development work in the field of Engineering and Applied Science. Articles published in Green Engineering are processed fully online. Submitted articles will go through peer review by a qualified international Reviewers. Complete information for article submission and other instructions are available in each issue. Green Engineering publishes 4 (four) issues a year in January, April, July and October, however articles that have been declared accepted will be queued in the In-Press issue before published in the determined time.
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 10 Documents
 1 
Evaluate the distribution of funds for corporate social responsibility Andika Danang Saputra; Putri Indah Lestari; Dina Febriyana Putri
Green Engineering: Journal of Engineering and Applied Science Vol. 1 No. 3 (2024): July : Green Engineering: International Journal of Engineering and Applied Scie
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70062/greenengineering.v1i3.8

Abstract

This study aims to evaluate the distribution of funds for corporate social responsibility (CSR). Through rigorous analysis, data on CSR spending from various companies is collected and evaluated. The aim is to understand the extent to which funds are allocated effectively to achieve CSR objectives, as well as to identify areas where improvements can be made. It is hoped that the findings of this study will provide valuable insights for companies in designing more effective and impactful CSR strategies.
Implementation Of Corporate Social Responsibility (CSR) By PT X To Improve The Company's Image Hanifah Diah Indriyaningrum; Rahma Dita Indriani; Diyah Nurhayati
Green Engineering: Journal of Engineering and Applied Science Vol. 1 No. 3 (2024): July : Green Engineering: International Journal of Engineering and Applied Scie
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70062/greenengineering.v1i3.10

Abstract

This study investigates the implementation of corporate social responsibility (CSR) by PT X with the aim of improving the company's image. Using a qualitative approach, data was collected through interviews and analysis of documents related to CSR. The findings highlight the CSR strategies adopted by PT The results of this research provide valuable insight into the importance of CSR in improving a company's image and provide recommendations for improving CSR implementation in the future.
Framework For Optimizing The Design of Reinforced Composite Products to Achieve Environmental Sustainability Christian Emeka Okafor; Godspower Onyekachukwu Ekwueme; Chibuzo Ndubuisi Okoye; Augustine Uzodinma Madumere; Calistus Princewill Odeh
Green Engineering: International Journal of Engineering and Applied Science Vol. 2 No. 1 (2025): January: Green Engineering: International Journal of Engineering and Applied Sc
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70062/greenengineering.v2i1.59

Abstract

In recognition of the need for sustainable design philosophies and practices that can be incorporated into the design of new products with an environmentally sustainable perspective throughout the life cycle, this research used a scoping review approach to x-ray the utility of the Sustainable Value Framework (SVF) in enhancing the application of reinforced composite products for ecological efficiency. An extensive search was performed using the electronic databases of articles such as PubMed, Google Scholar, Scopus, and Semantic Scholar. The study selected and extracted data from the literature according to the PRISMA-SCR (Preferred Reporting Items for Systematic Reviews and Meta-Analysis Extension for Scoping Reviews) to map the current literature for gaps in knowledge. The research studies show that SVF promotes the product design by incorporating characteristics such as environmental, economic, and social factors to attain optimal reduction of resources and sustainable uses of the environmental resources as well as improving the quality of the products. The study discussed the principles of sustainable value creation and their work evaluates new solutions of composite material selection, design method and technology for sustainable products. It also discusses policy drivers as well as industry and consumer practices with regards to reuse of surfaces in sustainable design. This study is beneficial to various stakeholders like the policymakers, the professionals in industries and construction, and the scholars.
Exploring Research Landscapes in Blockchain Logistics within Islamic Economics: A Bibliometric Study of Trends and Collaboration Networks Uswatun Kasanah, Yulinda; Miftahol Arifin
Green Engineering: International Journal of Engineering and Applied Science Vol. 2 No. 3 (2025): July : Green Engineering: International Journal of Engineering and Applied Scie
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70062/greenengineering.v2i3.199

Abstract

Blockchain logistics represents the integration of blockchain technology into the logistics sector, aiming to enhance efficiency, transparency, and security across supply chain processes. From an Islamic economics perspective, digital transformation must align with core values such as justice, transparency, and honesty to support the development of fair and sustainable logistics systems. The decentralized nature of blockchain offers promising solutions for building supply chains rooted in Islamic ethical principles. This study conducts a bibliometric analysis to examine the development and research trends of blockchain logistics within the context of Islamic economics. Using VOSviewer software, relevant scientific publications were analyzed based on bibliographic data sourced from reputable academic databases. Bibliometric parameters—such as the maximum number of authors per document and the minimum number of documents per author—were applied to identify key contributors and dominant research themes. The bibliometric mapping reveals the growth trajectory of blockchain logistics research framed by Islamic values. The visualization highlights research clusters, prominent authors, co-authorship networks, and publication trends that illustrate the evolution and scholarly interest in this interdisciplinary area. Emerging themes suggest a convergence between blockchain-driven logistics innovation and ethical economic practices advocated in Islamic teachings. The findings provide a comprehensive overview of the current landscape and collaboration opportunities in blockchain logistics research through an Islamic lens. This study contributes to the strategic positioning of future research by identifying gaps, potential synergies, and critical areas for development. Ultimately, it offers a foundational reference for scholars seeking to explore the integration of Islamic ethical principles within the advancement of blockchain-enabled logistics systems.
Water Level Monitoring Device with Hybrid Solar Power Based on IoT for River Safety Monitoring Mohammad Ilham Adi Saputra; Sri Arttini Dwi Prasetyowati; Sauqie Fairoozy Firdaus; Imam Rachmat Widodo
Green Engineering: International Journal of Engineering and Applied Science Vol. 2 No. 3 (2025): July : Green Engineering: International Journal of Engineering and Applied Scie
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70062/greenengineering.v2i3.217

Abstract

 The Karanggeneng River in Rembang Regency, Central Java, serves as the main water source for the surrounding community but is vulnerable to seawater contamination during the dry season due to decreasing river elevation. To address this issue, this study aims to design and implement a river water elevation monitoring device based on the Internet of Things (IoT) powered by a hybrid Solar Power Plant (PLTS). The device utilizes the MB7360 ultrasonic sensor connected to an ESP32 microcontroller to measure water elevation in real-time and display the data through an LCD and the Blynk application on a smartphone. The methodology includes literature review, device design, system implementation, and field performance testing. Test results show that the sensor can measure water height accurately within a range of 30 cm to 5 meters, and the PLTS system is capable of supplying the required 0.56 Watts of power. The study compared two alternative solutions and selected the ESP32-based system as the best option due to its efficiency, cost-effectiveness, and easy-to-source components. The conclusion of this research indicates that the developed device can provide accurate and continuous information, support monitoring of river conditions to prevent the risk of seawater intrusion, flooding, or drought, and has the potential to be applied as a mobile system in various other river locations across Indonesia.
Classification of Fatigue Levels of Tofu Industrial Workers Based on MOQS and Cardiovascular Load Variables Using Decision Tree Algorithm Intan Berlianty; Miftahol Arifin
Green Engineering: International Journal of Engineering and Applied Science Vol. 2 No. 3 (2025): July : Green Engineering: International Journal of Engineering and Applied Scie
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70062/greenengineering.v2i3.220

Abstract

Fatigue is a critical issue in labour-intensive small industries, especially in traditional food production such as tofu manufacturing. This study aims to develop a fatigue classification model using a decision tree algorithm by integrating subjective assessments of the work system through the Macroergonomic Organizational Questionnaire Survey (MOQS) and objective physiological indicators, specifically Cardiovascular Load (CVL). The research was conducted in a tofu home industry located in Kalisari Village, Banyumas, Indonesia. Primary data were collected from 10 workers through MOQS questionnaires and heart rate measurements taken at rest and during work. CVL values were calculated and used as labels for classification into three categories: low, moderate, and high fatigue. Meanwhile, MOQS dimension scores (organization, job, personal, environment, and technology) were transformed into interval data and used as classification features. A decision tree model was built using the CART algorithm and visualized for interpretability. The results show that all workers experienced at least moderate fatigue, with 20% categorized as high fatigue. The decision tree revealed that the dimensions of organizational and personal factors were the most influential in predicting fatigue levels. The model provides a practical and interpretable tool to support decision-making in scheduling, workload balancing, and ergonomic interventions. This study demonstrates a novel approach to combining macroergonomic assessments and physiological data with machine learning for practical fatigue risk management in small-scale food production environments.
Developing an Integer Linear Programming Model for Hotel Shift Scheduling: Empirical Insights from a Central Java Hotel Irwan Soejanto; Trismi Ristyowati; Indun Titisariwati
Green Engineering: International Journal of Engineering and Applied Science Vol. 2 No. 3 (2025): July : Green Engineering: International Journal of Engineering and Applied Scie
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70062/greenengineering.v2i3.221

Abstract

Employee shift scheduling in the hospitality industry remains a critical yet complex task due to fluctuating operational demands, fairness requirements, and labour regulations. Many hotels still rely on manual scheduling methods, which are time-consuming and prone to biases, particularly in ensuring fair workload distribution across employees. Despite numerous studies on workforce scheduling, limited attention has been given to integer linear programming (ILP) models that address gender-based restrictions and operational fairness simultaneously in real-world hotel contexts, especially in developing regions such as Central Java. This study proposes an Integer Linear Programming (ILP) model to generate optimal shift schedules for hotel staff over a 31-day planning horizon. The model incorporates operational constraints, including one shift per day, gender-based restrictions (which prevent female staff from working night shifts), availability, minimum staffing levels, and fairness in workload distribution. Key parameters and binary decision variables were defined to ensure compliance with the hotel's specific requirements. Empirical data were collected from a hotel in Central Java involving 20 employees, and the model was implemented using Python with a Gurobi solver. The ILP model successfully generated optimal schedules in under 10 seconds, significantly outperforming the manual method, which required over 4 hours. While the manual schedule resulted in an imbalance where some employees worked over 27 days and others only 22, the ILP approach enforced a strict maximum of 26 working days for all staff. Furthermore, the fairness index (FI) improved from 19.2% in the manual method to 0% in the ILP-generated schedule, indicating complete equity in workload allocation. The proposed ILP model demonstrates its effectiveness in improving scheduling fairness, operational efficiency, and compliance with labour policies. This work not only addresses a critical research gap in hospitality scheduling practices in Indonesia but also offers a replicable framework for other labour-intensive service sectors. Future research may explore multi-objective extensions incorporating employee preferences, satisfaction, and dynamic demand fluctuations.
Machine Learning Implementation for E-commerce Delivery Delay Prediction Using XGBoost Algorithm Stevanus Putra Lesmana; Dina Hermawati; Maulina Mukaromah; Iqbal Ahmad Bukhari; Norma Puspitasari
Green Engineering: International Journal of Engineering and Applied Science Vol. 2 No. 3 (2025): July : Green Engineering: International Journal of Engineering and Applied Scie
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70062/greenengineering.v2i3.219

Abstract

Delivery delays pose a major challenge in the e-commerce industry, often leading to decreased customer satisfaction and negatively impacting business operations. In this study, the XGBoost (Extreme Gradient Boosting) algorithm is applied to predict delivery delays based on a dataset containing 96,476 records. These records include various features relevant to the delivery process, such as shipping distance, carrier performance, and order characteristics. The model achieves a high overall accuracy of 93.24%, indicating strong general performance. In particular, XGBoost demonstrates excellent results in predicting on-time deliveries, achieving a precision of 93% and a recall of 100%. However, the model struggles to correctly identify delayed deliveries. The recall for delayed deliveries is 0%, and the F1-score is extremely low at 0.01. This significant discrepancy reveals a critical limitation in the model's performance — the inability to detect minority class cases (delayed deliveries) due to class imbalance within the dataset. The results highlight the importance of addressing data imbalance in predictive modeling for delivery outcomes. When the dataset is dominated by on-time delivery records, the model tends to be biased toward that class, failing to learn the patterns associated with delays. To improve performance, the study recommends integrating class balancing techniques such as SMOTE (Synthetic Minority Oversampling Technique) to generate synthetic samples of the minority class. Additionally, the use of alternative evaluation metrics beyond accuracy — such as precision, recall, and F1-score for each class — is suggested to provide a more comprehensive understanding of model effectiveness. Overall, the study provides valuable insights into the complexities of predicting delivery delays and outlines practical strategies for enhancing future models in e-commerce logistics analytics.
A Quantitative Well-to-Wheel Analysis of the Effect of Electric Vehicle Adoption on CO₂ Emissions in Indonesian Urban Logistics Miftahol Arifin; Dinda Natasya Artaviana
Green Engineering: International Journal of Engineering and Applied Science Vol. 2 No. 3 (2025): July : Green Engineering: International Journal of Engineering and Applied Scie
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70062/greenengineering.v2i3.223

Abstract

Urban logistics is a significant source of carbon emissions in Indonesia, and effective decarbonization strategies are required. EVs offer a promising solution, but their impact requires quantitative evaluation within the local context. This study analyzes the effect of adopting an electric van fleet on total well-to-wheel carbon emissions within an urban distribution network in Indonesia. This study employs a comparative case study method. A baseline scenario consisting of 25 diesel vans is compared to an intervention scenario where electric vans replace the entire fleet. The emission analysis was conducted using the WtW framework, utilizing specific emission factors for diesel fuel from the IPCC (2006) and the Java-Madura-Bali (JAMALI) grid emission factor from IESR (2023) to ensure contextual relevance. The transition to an electric fleet successfully reduces the total well-to-wheel carbon footprint by 13.63%. This reduction is equivalent to an absolute CO2 emission decrease of nearly 3 tons of CO₂ per month. Nevertheless, indirect emissions from electricity generation still contribute a significant carbon footprint, indicating that the national energy mix is highly dependent on the environmental benefits of EVs. This study concludes that fleet electrification is a viable and effective decarbonization strategy for Indonesia’s logistics sector, even with the current state of the electricity grid. However, fleet decarbonization efforts must run in parallel with policies for a national transition toward renewable energy to maximize the emission reduction potential of electric mobility. Future research should include the total cost of ownership (TCO) and life cycle assessment (LCA) for a more holistic evaluation.
Auto Tank Gauge System Analysis for Monitoring Stock Liquefied Petroleum Gas di integrated Palembang Terminal Muhammad Febrian Islami; Nita Nurdiana; Yudi Irwansi
Green Engineering: International Journal of Engineering and Applied Science Vol. 2 No. 3 (2025): July : Green Engineering: International Journal of Engineering and Applied Scie
Publisher : International Forum of Researchers and Lecturers

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70062/greenengineering.v2i3.222

Abstract

Measuring Liquefied Petroleum Gas (LPG) levels and inventory in storage tanks is a critical aspect of terminal operations, directly influencing safety, operational efficiency, and accurate stock management. The Integrated Terminal Palembang – Pulau Layang LPG Site has implemented a servo-type Automatic Tank Gauging (ATG) system, namely the Proservo NMS81, to provide precise and real-time volume measurements. Despite its operational importance, there remains a limited in-depth understanding of how this ATG system functions, particularly regarding the complete process from sensing LPG levels to converting them into accurate inventory data. This study aims to analyze the working mechanism of the Proservo NMS81 in measuring LPG height and generating digital stock data for monitoring purposes. The research method combines a literature review of the Proservo NMS81 technical datasheet and related scientific references with direct field observation (KSM-LP) at the LPG Pulau Layang site. The analysis covers the operating principle of the servo sensor, which relies on displacement measurement via a mechanical float and wire system; the analog-to-digital conversion process utilizing a 12-bit ADC to transform continuous signals into discrete digital values; the communication protocols employed, including HART and Modbus RS-485, for transmitting processed data to the control system; and the algorithmic data processing that converts tank level measurements into standardized inventory figures based on tank calibration tables and product density. The results of this study are expected to improve technical knowledge regarding servo-type ATG systems, enhance the accuracy and reliability of inventory monitoring, and contribute to more informed operational decision-making. Furthermore, the research findings are intended to serve as a valuable academic reference for the application of advanced instrumentation technology in the energy industry, supporting both professional practice and further scholarly exploration in the field.

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